meeg_utils.qc.Events#
- class meeg_utils.qc.Events(*, expected=None, stim_channel=None, min_interval=None)[source]#
Event counts and timing, compared with what the experiment should produce.
Events come from the annotations (excluding
BAD/EDGEannotations), or, if there are none, from the stimulus channel (mne.find_events()).- Parameters:
expected (dict | None) – Event name (annotation description, or trigger code as a string) mapped to the expected count. A different count is a
"fail".stim_channel (str | None) – Stimulus channel;
Noneuses MNE’s default channels.min_interval (float | None) – Shortest plausible interval between consecutive events, in seconds; shorter intervals are flagged (e.g. trigger bouncing).
- metrics_#
source("annotations"or the stimulus channel),counts,n_events,min_interval_s,n_simultaneous(events sharing a sample) andn_in_bad(events insideBADsegments).- Type:
Notes
Figures:
"timeline"(mne.viz.plot_events()).Methods
__init__(*[, expected, stim_channel, ...])compute(raw)Measure the recording.
get_metadata_routing()Get metadata routing of this object.
get_params([deep])Get parameters for this estimator.
not_applicable(raw)Return why the check cannot run on
raw, orNoneif it can.plot([kind, inst])Draw quality-control figures.
set_params(**params)Set the parameters of this estimator.
Attributes
levelThe worst verdict of the findings (
"ok"if there are none).modalitiesData types the check needs at least one of ("meg", "eeg").
Key of the check in reports.
kind -> whether it needs data (
inst).systemsAcquisition systems the check applies to;
Nonemeans all.